Denial-Of-Service Detection System

3. The system of claim 2, wherein the anomaly detection model is generated using a machine-learning algorithm that is included in the denial-of-service detection subsystem.

5. The system of claim 1, wherein the plurality of different storage system operating metrics include at least one storage system performance metric and at least one storage system network metric.

9. The IHS of claim 8, wherein the anomaly detection model is generated using a machine-learning algorithm that is included in the denial-of-service detection engine.

11. The IHS of claim 7, wherein the plurality of different storage system operating metrics include at least one storage system performance metric and at least one storage system network metric.

12. The IHS of claim 7, wherein the respective time-series of the current first storage system data for each of the plurality of different storage system operating metrics includes a covariance for the time-series, a Dynamic Time Warping (DTW) distance for the time-series, and a Shape-Based Distance (SBD) distance for the time series.

16. The method of claim 15, wherein the anomaly detection model is generated using a machine-learning algorithm that is included in the denial-of-service detection engine.

18. The method of claim 14, wherein the plurality of different storage system operating metrics include at least one storage system performance metric and at least one storage system network metric.

19. The method of claim 14, wherein the respective time-series of the current first storage system data for each of the plurality of different storage system operating metrics includes a covariance for the time-series, a Dynamic Time Warping (DTW) distance for the time-series, and a Shape-Based Distance (SBD) distance for the time series.